1. Field of the Invention
The present invention relates to techniques for camouflaging business-activity information in telemetry signals from a computer system. More specifically, the present invention relates to a method and an apparatus that monitors telemetry signals and generates artificial activity in a computer system to camouflage business-activity information in the telemetry signals.
2. Related Art
Modern server systems are typically equipped with a significant number of sensors which monitor signals during the operation of the server systems. For example, these monitored signals can include temperatures, voltages, currents, and a variety of software performance metrics, including CPU usage, I/O traffic, and memory utilization. Outputs from this monitoring process can be used to generate time series data for these signals which can subsequently be analyzed to determine how well a computer system is operating.
However, some telemetry signals gathered from certain enterprise servers may contain business-activity information, which a company would not want its competitors or unauthorized persons to learn. More specifically, by looking at these telemetry time series traces, it is possible to discover the level of a company's business activities and to infer company's business performance well before the company's CFO even knows how the company is doing.
For example, an enterprise server which executes business transactions for a company, such as company's booking, billing and shipping transactions, can generate a variety of telemetry signals which contain operating-system-related metrics such as load on CPU, throughput, I/O traffic, and response times. These telemetry signals have been shown to exhibit similar dynamic profiles including: (1) five large daily humps during typical business weeks with low troughs at nights and on weekends; (2) growing peak heights through a quarter; and (3) lower peak heights at the beginning of a new quarter (well-known “hockey stick” profiles from business metrics).
Such business dynamics show up in the telemetry time series because business activities are often reflected in the above-described operating system related metrics, which can be directly or indirectly obtained from the associated telemetry signals.
Even though none of company's sensitive information is accessible through such telemetry data, the fact that some of the telemetry time series dynamics reflect a company's level of business activity may create potentially serious business risks. For example, if this information falls into the wrong hands and is misused for financial gain, it could result in people going to jail and/or monetary damages to the company's business.
Although some telemetry signals can be extremely business-sensitive, these signals have not been generally considered to be confidential information. Consequently, such information can easily fall into the wrong hands, such as persons seeking financial gain in trading markets. Such persons, who can access this telemetry data, can come from both inside and outside of a company. For example, they can include employees, contractors, partners, interns, and hackers. Therefore, it is highly desirable to restrict access to this information by providing added business security to the telemetry signals.
Hence, what is need is a method and apparatus for effectively camouflaging business-activity information in telemetry data without the above-described problems.